public abstract class AbstractMetricMultiDimensionalPotentiallyPrecomputed extends AbstractMetricMultiDimensional
Metric.AggregateFunction
Modifier and Type | Method and Description |
---|---|
InformationLoss<?> |
createMaxInformationLoss()
Returns an instance of the maximal value.
|
InformationLoss<?> |
createMinInformationLoss()
Returns an instance of the minimal value.
|
Metric.AggregateFunction |
getAggregateFunction()
Returns the aggregate function of a multi-dimensional metric, null otherwise.
|
double |
getGeneralizationFactor()
Returns the factor used weight generalized values.
|
double |
getGeneralizationSuppressionFactor()
Returns the factor weighting generalization and suppression.
|
double |
getSuppressionFactor()
Returns the factor used to weight suppressed values.
|
boolean |
isIndependent()
Returns whether this metric requires the transformed data or groups to
determine information loss.
|
getMicroaggregationFunctions, getMicroaggregationStartIndex
createAECSMetric, createAECSMetric, createAmbiguityMetric, createDiscernabilityMetric, createDiscernabilityMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createHeightMetric, createHeightMetric, createKLDivergenceMetric, createLossMetric, createLossMetric, createLossMetric, createLossMetric, createMetric, createNormalizedEntropyMetric, createNormalizedEntropyMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedNormalizedEntropyMetric, createPrecomputedNormalizedEntropyMetric, createStaticMetric, createStaticMetric, getConfiguration, getDescription, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getName, initialize, isMonotonic, isMultiDimensional, isWeighted, list, toString
public InformationLoss<?> createMaxInformationLoss()
Metric
createMaxInformationLoss
in class AbstractMetricMultiDimensional
public InformationLoss<?> createMinInformationLoss()
Metric
createMinInformationLoss
in class AbstractMetricMultiDimensional
public Metric.AggregateFunction getAggregateFunction()
Metric
getAggregateFunction
in class AbstractMetricMultiDimensional
public double getGeneralizationFactor()
Metric
getGeneralizationFactor
in class Metric<AbstractILMultiDimensional>
public double getGeneralizationSuppressionFactor()
Metric
getGeneralizationSuppressionFactor
in class Metric<AbstractILMultiDimensional>
public double getSuppressionFactor()
Metric
getSuppressionFactor
in class Metric<AbstractILMultiDimensional>
public boolean isIndependent()
Metric
isIndependent
in class Metric<AbstractILMultiDimensional>